Prediction of Quinoa Grain Yield Using Machine Learning Models Based on Growth Traits and Yield Components under Deficit Irrigation and Organic Fertilization
Entessar Al-Jbawi*(1), Rasha Dannoura(²), and Abdullah Yacoub(³) (1). Sugar Beet Research Department, Crops Research Administration, General Commission for Scientific Agricultural Research (GCSAR), Damascus, Syria. (2). (GCSAR), Damascus, Syria. (3). Faculty of Agriculture, Department of Rural Engineering, Damascus University, Damascus, Syria. (*Corresponding author: dr.entessara@gmail.com or dr.entessara@gcsar.gov.sy). Received: 01/05/2026 Accepted: 15/06/2026 Abstract Machine learning (ML) Read More …